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|[[Generative Adversarial Networks (GAN)]] || 2014/06/10 || [[arxiv:1406.2661]] || || || [[GAN]] | |[[Generative Adversarial Networks (GAN)]] || 2014/06/10 || [[arxiv:1406.2661]] || || || [[GAN]] | ||
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|[[Very Deep Convolutional Networks for Large-Scale Image Recognition (VGGNet)]] || 2014/09/04 || [[arxiv:1409.1556]] || | |[[Very Deep Convolutional Networks for Large-Scale Image Recognition (VGGNet)]] || 2014/09/04 || [[arxiv:1409.1556]] || [[Computer Vision]] || || [[VGGNet]] | ||
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|[[Sequence to Sequence Learning with Neural Networks (Seq2Seq)]] || 2014/09/10 || [[arxiv:1409.3215]] || [[Natural Language Processing]] || || [[Seq2Seq]] | |[[Sequence to Sequence Learning with Neural Networks (Seq2Seq)]] || 2014/09/10 || [[arxiv:1409.3215]] || [[Natural Language Processing]] || || [[Seq2Seq]] | ||
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|[[Adam: A Method for Stochastic Optimization)]] || 2014/12/22 || [[arxiv:1412.6980]] || || || [[Adam]] | |[[Adam: A Method for Stochastic Optimization)]] || 2014/12/22 || [[arxiv:1412.6980]] || || || [[Adam]] | ||
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|[[Deep Residual Learning for Image Recognition (ResNet)]] || 2015/12/10 || [[arxiv:1512.03385]] || | |[[Deep Residual Learning for Image Recognition (ResNet)]] || 2015/12/10 || [[arxiv:1512.03385]] || [[Computer Vision]] || || [[ResNet]] | ||
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|[[Going Deeper with Convolutions (GoogleNet)]] || 2015/12/10 || [[arxiv:1409.4842]] || [[Computer Vision]] || [[Google]] || [[GoogleNet]] | |[[Going Deeper with Convolutions (GoogleNet)]] || 2015/12/10 || [[arxiv:1409.4842]] || [[Computer Vision]] || [[Google]] || [[GoogleNet]] | ||
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|[[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding]] || 2018/10/11 || [[arxiv:1810.04805]] || [[Natural Language Processing]] || [[Google]] || [[BERT]] | |[[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding]] || 2018/10/11 || [[arxiv:1810.04805]] || [[Natural Language Processing]] || [[Google]] || [[BERT]] | ||
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|[[Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context]] || 2019/01/09 || [[arxiv:1901.02860]] || || || [[Transformer-XL]] | |[[Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context]] || 2019/01/09 || [[arxiv:1901.02860]]<br>[https://github.com/kimiyoung/transformer-xl github] || || || [[Transformer-XL]] | ||
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|[[Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model (MuZero)]] || 2019/11/19 || [[arxiv:1911.08265]] || || || [[MuZero]] | |[[Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model (MuZero)]] || 2019/11/19 || [[arxiv:1911.08265]] || || || [[MuZero]] | ||
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|[[Language Models are Few-Shot Learners (GPT-3)]] || 2020/05/28 || [[arxiv:2005.14165]] || [[Natural Language Processing]] || [[OpenAI]] || [[GPT-3]] | |[[Language Models are Few-Shot Learners (GPT-3)]] || 2020/05/28 || [[arxiv:2005.14165]] || [[Natural Language Processing]] || [[OpenAI]] || [[GPT-3]] | ||
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|[[An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (ViT)]] || 2020/10/22 || [[arxiv:2010.11929]] || [[Computer Vision]] || | |[[An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (ViT)]] || 2020/10/22 || [[arxiv:2010.11929]]<br>[https://github.com/google-research/vision_transformer GitHub] || [[Computer Vision]] || [[Google]] || [[Vision Transformer]] ([[ViT]]) | ||
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|[[Learning Transferable Visual Models From Natural Language Supervision (CLIP)]] || 2021/02/26 || [[arxiv:2103.00020]]<br>[https://openai.com/blog/clip/ OpenAI Blog] || [[Computer Vision]] || | |[[Learning Transferable Visual Models From Natural Language Supervision (CLIP)]] || 2021/02/26 || [[arxiv:2103.00020]]<br>[https://openai.com/blog/clip/ OpenAI Blog] || [[Computer Vision]] || [[OpenAI]] || [[CLIP]] | ||
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|[[MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer]] || 2021/10/05 || [[arxiv:2110.02178]] || [[Computer Vision]] || | |[[MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer]] || 2021/10/05 || [[arxiv:2110.02178]]<br>[https://github.com/apple/ml-cvnets GitHub] || [[Computer Vision]] || [[Apple]] || [[MobileViT]] | ||
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|[[Block-Recurrent Transformers]] || 2022/03/11 || [[arxiv:2203.07852]] || || || | |[[Block-Recurrent Transformers]] || 2022/03/11 || [[arxiv:2203.07852]] || || || |